Interface ISageMakerCreateEndpointConfigJsonPathProps

public interface ISageMakerCreateEndpointConfigJsonPathProps : ITaskStateJsonPathBaseProps, IStateBaseProps, ITaskStateBaseOptions, IAssignableStateOptions, IJsonPathCommonOptions

Syntax (vb)

Public Interface ISageMakerCreateEndpointConfigJsonPathProps Inherits ITaskStateJsonPathBaseProps, IStateBaseProps, ITaskStateBaseOptions, IAssignableStateOptions, IJsonPathCommonOptions

Remarks

See: https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html

ExampleMetadata: fixture=_generated

Examples

// The code below shows an example of how to instantiate this type.
             // The values are placeholders you should change.
             using Amazon.CDK;
             using Amazon.CDK.AWS.EC2;
             using Amazon.CDK.AWS.StepFunctions;
             using Amazon.CDK.AWS.StepFunctions.Tasks;
             using Amazon.CDK.Interfaces.KMS;

             AcceleratorType acceleratorType;
             var assign;
             InstanceType instanceType;
             IKeyRef keyRef;
             var resultSelector;
             TaskInput taskInput;
             TaskRole taskRole;
             Timeout timeout;

             var sageMakerCreateEndpointConfigJsonPathProps = new SageMakerCreateEndpointConfigJsonPathProps {
                 EndpointConfigName = "endpointConfigName",
                 ProductionVariants = new [] { new ProductionVariant {
                     InstanceType = instanceType,
                     ModelName = "modelName",
                     VariantName = "variantName",

                     // the properties below are optional
                     AcceleratorType = acceleratorType,
                     InitialInstanceCount = 123,
                     InitialVariantWeight = 123
                 } },

                 // the properties below are optional
                 Assign = new Dictionary<string, object> {
                     { "assignKey", assign }
                 },
                 Comment = "comment",
                 Credentials = new Credentials {
                     Role = taskRole
                 },
                 Heartbeat = Duration.Minutes(30),
                 HeartbeatTimeout = timeout,
                 InputPath = "inputPath",
                 IntegrationPattern = IntegrationPattern.REQUEST_RESPONSE,
                 KmsKey = keyRef,
                 OutputPath = "outputPath",
                 QueryLanguage = QueryLanguage.JSON_PATH,
                 ResultPath = "resultPath",
                 ResultSelector = new Dictionary<string, object> {
                     { "resultSelectorKey", resultSelector }
                 },
                 StateName = "stateName",
                 Tags = taskInput,
                 TaskTimeout = timeout,
                 Timeout = Duration.Minutes(30)
             };

Synopsis

Properties

EndpointConfigName	The name of the endpoint configuration.
KmsKey	AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.
ProductionVariants	An list of ProductionVariant objects, one for each model that you want to host at this endpoint.
Tags	Tags to be applied to the endpoint configuration.

Properties

EndpointConfigName

The name of the endpoint configuration.

string EndpointConfigName { get; }

Property Value

string

Remarks

See: https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html

ExampleMetadata: fixture=_generated

KmsKey

AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

IKeyRef? KmsKey { get; }

Property Value

IKeyRef

Remarks

Default: - None

ProductionVariants

An list of ProductionVariant objects, one for each model that you want to host at this endpoint.

IProductionVariant[] ProductionVariants { get; }

Property Value

IProductionVariant[]

Remarks

Identifies a model that you want to host and the resources to deploy for hosting it. If you are deploying multiple models, tell Amazon SageMaker how to distribute traffic among the models by specifying variant weights.